Stratiform and Convective Classification of Rainfall Using SSM/I 85-GHz Brightness Temperature Observations

Abstract A better understanding of global climate calls for more accurate estimates of liquid and ice water content profiles of precipitating clouds and their associated latent heating profiles. Convective and stratiform precipitation regimes have different latent heating and therefore impact the earth’s climate differently. Classification of clouds over oceans has traditionally been part of more general rainfall retrieval schemes. These schemes are based on individual or combined visible and infrared, and microwave satellite observations. However, none of these schemes report validations of their cloud classification with independent ground observations. The objective of this study is to develop a scheme to classify convective and stratiform precipitating clouds using satellite brightness temperature observations. The proposed scheme probabilistically relates a quantity called variability index (VI) to the stratiform fractional precipitation coverage over the satellite field of view (FOV). The VI for a s...

[1]  Matthias Steiner,et al.  Climatological Characterization of Three-Dimensional Storm Structure from Operational Radar and Rain Gauge Data , 1995 .

[2]  Thomas H. Vonder Haar,et al.  A Bispectral Method for Cloud Parameter Determination , 1977 .

[3]  Judith A. Curry,et al.  Classification of clouds over the western equatorial Pacific Ocean using combined infrared and microwave satellite data , 1995 .

[4]  P. Webster,et al.  TOGA COARE: The Coupled Ocean-Atmosphere Response Experiment. , 1992 .

[5]  Gerald R. North,et al.  Sampling Error Study for Rainfall Estimate by Satellite Using a Stochastic Model , 1988 .

[6]  Darren L. Jackson,et al.  A physical retrieval of cloud liquid water over the global oceans using special sensor microwave/imager (SSM/I) observations , 1993 .

[7]  W. Rossow,et al.  ISCCP Cloud Data Products , 1991 .

[8]  Robert F. Adler,et al.  A Proposed Tropical Rainfall Measuring Mission (TRMM) Satellite , 1988 .

[9]  Russell L. Martin,et al.  Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model , 1990 .

[10]  Toshiro Inoue,et al.  A cloud type classification with NOAA 7 split‐window measurements , 1987 .

[11]  J. Mitchell,et al.  C02 and climate: a missing feedback? , 1989, Nature.

[12]  W. Shenk,et al.  A multispectral cloud type identification method using Nimbus 3 MRIR measurements. , 1972 .

[13]  G. North,et al.  Sampling Errors in Satellite Estimates of Tropical Rain , 1987 .

[14]  Grant W. Petty.  On the Response of the Special Sensor Microwave/Imager to the Marine Environment: Implications for Atmospheric Parameter Retrievals. Ph.D. Thesis , 1990 .

[15]  J. Curry,et al.  Retrieval of precipitation from satellite microwave measurement using both emission and scattering , 1992 .

[16]  Christopher S. Ruf,et al.  Determination of cloud liquid water content using the SSM/I , 1990 .

[17]  C. Sui,et al.  Heating, Moisture, and Water Budgets of Tropical and Midlatitude Squall Lines: Comparisons and Sensitivity to Longwave Radiation , 1993 .

[18]  David A. Short,et al.  The beam filling error in the Nimbus 5 electronically scanning microwave radiometer observations of Global Atlantic Tropical Experiment rainfall , 1990 .

[19]  E. Anagnostou,et al.  Radar Rainfall Estimation for Ground Validation Studies of the Tropical Rainfall Measuring Mission , 1997 .

[20]  Robert F. Adler,et al.  Retrieval Algorithms for Estimating the Vertical Profiles of Latent Heat Release: Their Applications for TRMM@@@TRMMへの応用 , 1993 .